Seismic signal processing and exploration

ABSTRACT

An apparatus and method for the exploration of hydrocarbons by obtaining a set of seismic signal traces distributed over a pre-determined three-dimensional volume of the earth and using a computer to: divide the three-dimensional volume into a plurality of vertically stacked and generally spaced apart horizontal slices; divide each of the slices into a plurality of cells having portions of at least three seismic traces located therein; measure the cross-correlation between one pair of traces lying in one vertical plane to obtain an in-line value and the cross-correlation between another pair of traces lying in another vertical plane to obtain a cross-line value; and combine the in-line value and the cross-line value to obtain one coherency value for each of the cells; and display the coherency values.

CROSS-REFERENCE

This application is a continuation of a U.S. patent application that wasfiled on Oct. 1, 1996 under Ser. No. 716,612 and that is now U.S. Pat.No. 5,838,564 which was a continuation of a U.S. patent applicationfiled on Dec. 12, 1994 under Ser. No. 08/353,934 and that is now U.S.Pat. No. 5,563,949.

TECHNICAL FIELD

This invention relates to the general subject of seismic explorationand, in particular, to apparatus and methods for identifying structuraland stratigraphic features in three dimensions.

BACKGROUND OF THE INVENTION

Ordinary 2-D seismic data is acquired along lines (See lines 10 and 11in FIG. 1) that consist of geophone arrays onshore or hydrophonestreamer traverses offshore. Geophones and hydrophones act as sensors toreceive energy that is transmitted into the ground and reflected back tothe surface from subsurface rock interfaces 12. Energy is usuallyprovided onshore by vibroseis vehicles which transmit pulses by shakingthe ground at pre-determined intervals and frequencies on the surface.Offshore, airgun sources are usually used. Subtle changes in the energyreturned to surface often reflect variations in the stratigraphic,structural and fluid contents of the reservoirs.

In 3-D seismic the principle is similar, however, lines and arrays aremore closely spaced (See FIGS. 1 and 2) to provide more detailedsub-surface coverage. With this high density coverage, extremely largevolumes of digital data need to be recorded, stored and processed beforefinal interpretation can be made. Processing requires extensive computerresources and complex software to enhance the signal received from thesubsurface and to mute accompanying noise which masks the signal.

Once the data is processed, geophysical staff compile and interpret the3-D seismic information in the form of a 3-D cube (See FIG. 4) whicheffectively represents a display of subsurface features. Using the datacube, information can be displayed in various forms. Horizontal timeslice maps can be made at selected depths (See FIG. 5). Using a computerworkstation an interpreter can slice through the field to investigatereservoir issues at different horizons. Vertical slices or sections canalso be made in any direction using seismic or well data. Time maps canbe converted to depth to provide a structural interpretation at aspecific level.

Three-dimensional (3-D) seismic is being used extensively worldwide toprovide a more detailed structural and stratigraphic image of subsurfacereservoirs. Acceptance of 3-D seismic has accelerated during the lastfive years based on a proven track record that continues to grow. The3-D payout has been measured by increased reserve estimates, costsavings from more accurate positioning of delineation and developmentwells, improved reservoir characterization leading to better simulationmodels, and the ability to predict more accurately future opportunitiesand problems during the production history of a field. More importantly,3-D seismic has also been used as an exploration tool to reduce drillingrisk in structurally complex areas and to predict reservoir quality inundrilled areas.

As good as 3-D seismic surveys and interpreters have become,improvements are needed.

In particular, seismic data has been traditionally acquired andprocessed for the purpose of imaging seismic reflections. Changes instratigraphy are often difficult to detect on traditional seismicdisplays due to the limited amount of information that stratigraphicfeatures present in a cross-section view. Although such views provide anopportunity to see a much larger portion of these features, it isdifficult to identify fault surfaces within a 3-D volume where no faultreflections have been recorded. More importantly, seismic data is notknown to have been acquired or used for the purpose of imaging seismicdiscontinuities instead of seismic reflections.

SUMMARY OF THE INVENTION

In accordance with the present invention, a method is disclosed for theexploration of hydrocarbons. The method comprises the steps of:obtaining a set of seismic signal traces distributed over apre-determined three-dimensional volume of the earth; dividing thethree-dimensional volume into a plurality of vertically stacked andgenerally spaced apart horizontal slices; dividing each of the slicesinto a plurality of cells that are arranged into laterally extendingrows and columns and that have portions of at least three generallyvertically extending seismic traces located therein; measuring acrosseach of the cells the cross-correlation between one pair of traces lyingin one vertical plane to obtain an in-line value and measuring thecross-correlation between another pair of traces lying in anothervertical plane to obtain a cross-line value that are estimates of thetime dip in an in-line direction and in a cross-line direction;combining the in-line value and the cross-line value to obtain onecoherency value for each of the cells; and displaying the coherencyvalues of the cells across at least one horizontal slice.

This technique is particularly well suited for interpreting fault planeswithin a 3-D seismic volume and for detecting subtle stratigraphicfeatures in 3-D. This is because seismic traces cut by a fault linegenerally have a different seismic character than traces on either sideof the fault. Measuring trace similarity, (i.e., coherence or 3-Dcontinuity) along a time slice reveals lineaments of low coherence alongthese fault lines. Such coherency values can reveal critical subsurfacedetails that are not readily apparent on traditional seismic sections.Also by calculating coherence along a series of time slices, these faultlineaments identify fault planes or surfaces.

Numerous other advantages and features of the present invention willbecome readily apparent from the following detailed description of theinvention, the embodiments described therein, from the claims, and fromthe accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an arrangement of geophones to obtain 3-D seismicdata from the earth's subsurface for processing in accordance with thepresent invention;

FIG. 2 is a plan view of the arrangement shown in FIG. 1;

FIG. 3 is a representation of the seismic traces laying in a planepassing through one row of geophones shown in FIG. 2;

FIG. 4 is a pictorial representation of the information obtained fromprocessing 3-D seismic data;

FIG. 5 is a pictorial representation of a horizontal time slice of 3-Dseismic data processed in accordance with the prior art;

FIG. 6 is a pictorial representation of a horizontal time slice of 3-Dseismic data processed in accordance with the present invention;

FIG. 7 is a simplified flow chart depicting the process of theinvention; and

FIG. 8 is a schematic diagram depicting one embodiment of the invention.

DETAILED DESCRIPTION

While this invention is susceptible of embodiment in many differentforms, there is shown in the drawings, and will herein be described indetail, one specific embodiment of the invention. It should beunderstood, however, that the present disclosure is to be considered anexemplification of the principles of the invention and is not intendedto limit the invention to the specific embodiment or algorithm sodescribed.

The first step is to obtain a set of seismic data in the form of seismicsignal traces distributed over a three dimensional volume of the earth.Methods by which such data is obtained and reduced to digital form forprocessing as 3-D seismic data are well known to those skilled in theart.

Referring to FIG. 7, the next step is to generate a "discontinuitycube." This is done by applying a coherency algorithm to the 3-D seismicdata. This algorithm may take many forms. Whatever its form, itsfunction is to compare the similarity of nearby regions of seismic datawithin the 3-D seismic volume. If a trace segment is similar to itsneighbors (e.g., in the in-line and cross-line directions), it isassigned a low discontinuity value; if a trace segment is not similar toits neighbors, it is assigned a high discontinuity value.

FIG. 2 is a plan view of a portion of 3-D seismic volume. In order tomeasure discontinuity, a trace segment at one point A is compared toadjacent trace segments B and C. One way to compute trace similarity isdescribed below.

The zero mean lagged cross-correlation in the in-line (x-direction)between trace u(t, x, y) and u(t, x+dx, y) with a lag time of "tlag"msec is defined as: ##EQU1## where: ##EQU2## and ##EQU3## areauto-correlations used to normalize the cross-correlation, and where w+wis the length in msec of the correlation window. It is important tochoose w large enough so the assumption of zero mean is valid. Values onthe order of a seismic wavelet are appropriate. Other methods ofnormalization may be used (e.g., product of the energies of the traces,etc.). In particular, cross correlation is one method of combining twowaveforms to measure the similarities of the waveforms. Auto-correlationis a method of combining a waveform with itself. See Sheriffs"Encyclopedic Dictionary of Exploration Geophysics," Society ofExploration Geophysicists, Tulsa, Okla.

The zero mean lagged cross-correlation in the cross-line (y-direction)between trace u(t, x, y) and u(t, x, y+dy) with a lag time of tlag msecis defined as: ##EQU4## where: ##EQU5##

The direction of apparent time dip in the x and y directions isestimated to be that lag (i.e., tlagx and tlagy) that has the greatest(i.e., most positive) cross-correlation. These values are ρ_(x) (t,tlagx) and ρ_(y) (t, tlagy).

Given the apparent dips (in msec/trace), it is a simple (but notnecessarily accurate when dealing with noisy data) calculation to obtaindip and dip azimuth. More importantly, the concept of cross-correlationis extended to two dimensions by taking the geometric mean between theclassical one dimensional cross-correlations: ##EQU6##

This value (or seismic attribute) serves as a rather robust estimate ormeasure of signal discontinuity within geologic formations as well assignal discontinuities across faults and erosional unconformities. Othermethods may be used to combine one dimensional cross-correlations (e.g.,arithmetic mean, root mean square, average, median, square root of thesum of the squares, square root of the product of the squares, minimum,maximum, sum, product, etc.). The geometric mean has been found toperform quite satisfactorily. The main point is that inline andcrossline information are combined to produce a "3D" measurement.

Computer Program

A simplified FORTRAN 77 program for performing these calculations isgiven below: Given a trace "x" from a 3-D seismic amplitude volume, andits two neighboring traces "y" (in the in-line direction) and "z" (inthe cross-line direction), subroutine COH calculates an output trace"rho" containing coherence coefficients using a running windowcross-correlation algorithm where:

"mins" and "maxs" are the minimum and maximum sample indices for allfour traces;

"inwinl" is the window length in samples;

"nlags" specifies the number of lags (relative time shifts) to do eachside of "0" in the cross-correlation; and

"sr" is the sample interval in ms.

At each sample, subroutine CROSS calculates a series of normalizedcross-correlation coefficients, returning the largest coefficients foreach direction in "rho1" and "rho2". The time shift at which the maximumcoefficients occur is returned in "tshf1" and "tshf2"; these times arenot used. Subroutine COH is called repeatedly, once for every trace inthe input seismic amplitude volume, to produce a new 3-D data volume or"coherency cube" containing coherence coefficients.

    ______________________________________                                        subroutine COH (x, y, z, rho, mins, maxs, iwinl, nlags, sr)                   real x(mins: maxs), y(mins: maxs), z(mins: maxs)                              real rho(mins: maxs)                                                          ihwin = iwinl/2                                                               do j = mins + ihwin, maxs - ihwin                                             k = j - ihwin                                                                 call CROSS (x(k), iwinl, y(k), iwinl, nlags, sr, rho1, tshf1)                 call CROSS (x(k), iwinl, z(k), iwinl, nlags, sr, rho2, tshf2)                 rho(J) = sqrt (rho1 * rho2)                                                   enddo                                                                         return                                                                        end                                                                           subroutine CROSS (x, nx, y, ny, lags, sr, peak, tshift)                       real x(0:nx-1), y(0:ny-1), sr, peak, tshift                                   parameter (maxlags = 128)                                                     real g(-maxlags: +maxlags)                                                    double precision xx, yy                                                       nlags = max(0, min(lags, maxlags))                                            tshift = 0.0                                                                  peak = 0.0                                                                    xx = 0.0                                                                      yy = 0.0                                                                      ks = 0                                                                        do ix = 0, nx-1                                                               xx = x(ix)**2+xx                                                              enddo                                                                         if (xx .eq. 0.0) return                                                       do iy = 0, ny-1                                                               yy = y(iy)**2 + yy                                                            enddo                                                                         if (yy .eq. 0.0) return                                                       do is = -nlags, + nlags                                                       g(is) = 0.0                                                                   do it = 0, nx-1                                                               if (it - is .ge. 0) then                                                      if (it - is .le. ny - 1)then                                                  g(is) = g(is) + x(it) * y(it - is)                                            endif                                                                         endif                                                                         enddo                                                                         if (abs(peak) .lt. abs(g(is))) then                                           peak = g(is)                                                                  ks = is                                                                       endif                                                                         enddo                                                                         tshift = ks * sr                                                              peak = peak/sqrt (xx * yy)                                                    return                                                                        end                                                                           ______________________________________                                    

Landmark and GeoQuest interpretive workstations, for example, can beused (see FIG. 8) to view and interpret faults and stratigraphicfeatures by loading the discontinuity cube as a seismic volume. Suchworkstations are commonly are used by those skilled in the art. Themethod of the invention can be conveniently loaded onto the workstationby means of a magnetic tape or disk which has been encoded withinstructions for the computer to perform the above-described process.Visualization software (e.g., Landmark's SeisCube software) may beemployed to rapidly slice through the discontinuity volume to aid inunderstanding complex fault relationships. Discontinuity displays,including printouts in the form of seismic attribute maps, can reduceinterpretation cycle time when used in selecting which seismic lines tointerpret, enabling the interpreter to work around faults and poor dataareas. In addition, subtle stratigraphic features and complex faultingwhich are not readily apparent on traditional seismic displays can berapidly identified and interpreted. FIGS. 5 and 6 are side by sidecomparisons of the same seismic information displayed and processedconventionally and in accordance with the present invention. Fault linesare readily apparent in FIG. 6.

Coherency maps have been run on several 3-D surveys. At depths ofreasonable data quality, approximately 90% of the faults can be readilyidentified. Faults were identified on coherency maps which were verysubtle on seismic sections, but clearly present on the coherency mapsbecause of the robustness of the method and the map perspective of faultpatterns. Since coherency maps can be run on uninterpreted time slices,the present invention offers a means to greatly accelerate mapping ofthe structural framework and to reveal details of fault relationshipswhich would otherwise be interpreted only through tedious fault picking.

SPECIFIC EXAMPLES

2-D seismic coherence maps were generated along picked horizons andclearly identified shale diapirs in offshore Nigeria.

In offshore Gulf of Mexico, the technique readily identified diapiricstructures.

On several coherence time slices, remarkable detail of stratigraphicfeatures, such as abandoned river channels, mud flows, and submarinecanyons, was displayed. On seismic sections, these features weresometimes apparent but, in some cases, were unidentifiable even withclose scrutiny.

This is the first known method of revealing fault planes within a 3-Dvolume where no fault reflections have been recorded. Faults are oftencritical to the accumulation of oil. A fault may form a seal by cuttingoff a structural or stratigraphic feature so the oil is trapped againstthe fault. On the other hand, if the fault plane contains rubble thathas not been cemented, it may form a conduit for fluids. This may allowthe hydrocarbons to drift up the fault plane into the feature and betrapped in it or to escape from the feature by drifting up the faultplane out of it. Thus, fault lines can predict flow patterns in areservoir and communication between injector and producing wells, forexample.

Seismic discontinuities can also provide the needed link to enablereservoir prediction between the wells and establish reservoircontinuity and flow patterns across a field. Coherency technology can beused for finding, identifying and mapping of subsurface features whichare commonly associated with the entrapment and storage of hydrocarbons.

Coherency mapping of 3-D seismic is an extremely powerful and efficienttool for mapping both structure and stratigraphy. The new method isparticularly sensitive to any lateral variation in wavelet character andtherefore is particularly sensitive to the common causes of lateralvariations in the wavelet (i.e., fault displacement or stratigraphicvariations). This 3-D method analyzes a time-slice or horizon basedinterval and measures the maximum of the normalized cross-correlation inthe in-line and cross-line directions.

From the foregoing description, it will be observed that numerousvariations, alternatives and modifications will be apparent to thoseskilled in the art. Accordingly, this description is to be construed asillustrative only and is for the purpose of teaching those skilled inthe art the manner of carrying out the invention. Other algorithms maybe used to measure the similarity of nearly regions of seismic data orto generate the "discontinuity cube." Thus, it should be understood thatcross correlation is but one mathematical method that may be used tocompute the coherence/similarity of seismic signals. Equivalentcomputations (e.g., covariance, etc.) may be substituted for thosespecifically illustrated and described. Finally, it should be understoodthat the cross correlation, or equivalent, may or may not be normalized.

Also certain features of the invention may be used independently ofother features of the invention. For example, stratigraphic featureshave been generally identified on time slices where dips were low; andconsequently, the time window captured a narrow statigraphic section. Inareas of higher dip, the method should work on picked horizons.Therefore, as a stratigraphic mapping tool, there is good reason tobelieve that new levels of detail can be mapped than previously,although this may require mapping of the horizon of interest.

As another example, while coherence slice maps by themselves are verypowerful mapping tools, when used in conjunction with reconnaissancemapping of amplitudes and dip maps, there is promise of a technologicalmilestone in mapping effectiveness for the Gulf of Mexico or similarbasins with 3-D seismic. It is believed that detailed mapping ofstructure and stratigraphy will be accelerated by mapping in a map viewand less by traditional line by line picking. Interpretation in a mapview of "reconnaissance" data offers significant improvement in qualityand quantity of interpretation.

Thus it will be appreciated that various modifications, alternatives,variations, and changes may be made without departing from the spiritand scope of the invention as defined in the appended claims. It is, ofcourse, intended to cover by the appended claims all such modificationsinvolved within the scope of the claims.

We claim:
 1. In a computer workstation wherein 3-D seismic data is readinto memory and divided into a plurality of samples of at least threeseparated seismic traces, and wherein the computer is used to transformsuch data into a display of seismic attributes to identify subsurfacefeatures commonly associated with the entrapment and storage ofhydrocarbons, the computer being programmed to perform a processcomprising the steps of:(1) measuring the coherency/similarity ofsamples of at least three seismic traces relative to two pre-determineddirections; and (2) storing said coherency/similarity of said samplesfor displaying in the form of at least a two-dimensional map.
 2. Thecomputer workstation of claim 1, where in step (1) the computer isprogrammed to measure said coherency/similarity of said three samples asa function of the cross-correlation between at least two of said threesamples along one line of reference and the cross-correlation between atleast two of said three samples along a line of reference that isperpendicular to said one line of reference.
 3. The computer workstationof claim 2, where in step (1) the computer is programmed to measure saidcoherency/similarity of said samples in terms of the largestcross-correlation along each of said two lines of reference.
 4. Thecomputer workstation of claim 3, where in step (1) the computer isprogrammed to measure said coherency/similarity of said samples as afunction of the geometric mean of the least cross-correlation in each ofsaid two lines of reference.
 5. The computer workstation of claim 1,wherein the workstation comprises a video display; wherein said samplesare formed from said traces by dividing said traces relative to aplurality of vertically separated relatively horizontal lines; andfurther including the step of using the computer and said video displayto depict the coherencies/similarities of successive verticallyseparated samples to identify relative space and time invariantfeatures.
 6. The computer workstation of claim 1, where in step (1) thecomputer is programmed to measure said coherency/similarity of saidsamples by:(i) determining cross-correlations in an in-line directionbetween a first trace sample and a second trace sample, and determiningthe cross-correlations in a cross-line direction between said firsttrace sample and a third trace sample; (ii) identifying at least one ofsaid cross-correlations in said in-line direction and at least one ofsaid cross-correlations in said cross-line direction in accordance witha pre-determined criteria; and (iii) combining said at least oneidentified cross-correlation in said in-line direction and said at leastone identified cross-correlation in said cross-line direction.
 7. Thecomputer workstation of claim 6, wherein the computer is programmed toperform step (ii) by identifying the most positive of saidcross-correlations in said in-line direction and the most positive ofsaid cross-correlations in said cross-line direction.
 8. The computerworkstation of claim 6, wherein the computer is programmed to performstep (iii) by computing a mean of said identified cross-correlations insaid in-line direction and in said cross-line direction.
 9. The computerworkstation of claim 1, where in step (1) the computer is programmed tomeasure said coherency/similarity of said samples by: determining thezero mean lagged cross-correlation in an in-line direction betweensamples of a first trace and samples of a second trace; and determiningthe zero mean lagged cross-correlation in a cross-line direction betweensaid samples of a first trace and samples of a third trace.
 10. Thecomputer workstation of claim 1, wherein the workstation comprises avideo monitor; and wherein said process further includes the step of:(3)displaying on said video monitor said posted coherency/similarity valuesof step (2).
 11. In the exploration for hydrocarbons wherein 3-Dgeophysical data is accessed and divided into a plurality of samples ofseismic traces, and wherein such geophysical data is transformed by acomputer into a visual display of seismic attributes, a processcomprising the steps of:(1) for a trace sample selected in accordancewith a pre-determined criteria, measuring representations ofcross-correlations between it and at least one cross-line trace sampleand measuring representations of cross-correlations between it and atleast one in-line trace sample; (2) for each selected trace sample,identifying at least one of said representations of cross-correlation insaid in-line direction and at least one of said representations ofcross-correlation in said cross-line direction in accordance with apre-determined criteria; (3) combining said identified cross-correlationin said in-line direction and said identified cross-correlation in saidcross-line direction; (4) repeating steps (1) through (3) in accordancewith said pre-determined trace sample selection criteria; and (5)displaying said combined cross-correlations of said selected tracesamples in the form of at least a two-dimensional map.
 12. The processof claim 11, wherein said 3-D geophysical data is obtained over apre-determined three-dimensional volume of the earth; wherein saidpre-determined trace sample selection criteria comprises trace sampleslying between two planes passing through said three-dimensional volumeof the earth; and wherein said process further includes the step ofdisplaying said combined cross-correlations of successive verticallyseparated trace samples.
 13. The process of claim 11, wherein thecomputer is programmed to perform step (2) by identifying the mostpositive of said cross-correlations in said in-line direction and themost positive of said cross-correlations in said cross-line direction.14. The process of claim 11, wherein the computer is programmed toperform step (3) by computing the geometric mean of said identifiedcross-correlation in said in-line direction and said identifiedcross-correlation in said cross-line direction.
 15. The process of claim11, wherein the computer is programmed to perform step (1) bydetermining the zero mean lagged cross-correlation in an in-linedirection between said selected trace sample and an adjacent tracesample lying in said in-line direction and by determining the zero meanlagged cross-correlation in a cross-line direction between said selectedtrace sample and an adjacent trace sample lying in said cross-linedirection.
 16. A workstation wherein geophysical data obtained over apre-determined three-dimensional volume is read into a memory, whereinsuch data is arranged into an array of trace samples, and wherein acomputer is used to transform such data into a display of geophysicalattributes, the computer being instructed by a program to perform aprocess, comprising the steps of:(1) measuring, relative to a selectedtrace sample, the similarity between it and a second trace sample andthe similarity between it and at least a third trace sample; (2)combining said measured similarities to obtain one measurement thatcharacterizes the coherency of said selected trace sample; (3) repeatingsteps (1) and (2) for selected trace samples in at least one of thein-line and cross-line directions; and (4) posting said combinedmeasurements of similarity for display.
 17. The process of claim 16,wherein step (1) is performed by measuring the zero mean laggedcross-correlation in one direction between said selected trace sampleand said second trace sample and measuring the zero mean laggedcross-correlation in at least one other direction between said firstselected trace sample and said third trace sample.
 18. The process ofclaim 17, wherein said one direction is the in-line direction; andwherein said other direction is the in the cross-line direction.
 19. Theprocess of claim 18, wherein step (2) comprises the steps of identifyinga positive cross-correlation in said in-line direction, and identifyinga positive cross-correlation in said cross-line direction.
 20. Theprocess of claim 19, wherein step (2) comprises the step of computingthe geometric mean of said positive cross-correlation in said in-linedirection and said positive cross-correlation in said cross-linedirection.